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ERP Migration

The Importance of Parallel Running During ERP System Transition

Learn how parallel running mitigates risk in ERP migrations by validating data integrity, process accuracy, and system stability before cutover.

6 min readSysGenPro Editorial
The Importance of Parallel Running During ERP System Transition

Parallel Running Is the Critical Validation Phase for ERP Migration Success

Parallel running is the operational phase where both the legacy and new ERP systems process live business transactions simultaneously. This approach is essential for validating data integrity, process accuracy, and system stability before the final cutover. By operating both systems in tandem, organizations can identify discrepancies in financial reporting, inventory levels, and customer data without disrupting daily operations. The primary risk of skipping this phase is undetected data corruption or process failures that only surface after the legacy system is decommissioned, leading to significant financial loss and operational downtime. Effective parallel running requires a structured plan, clear reconciliation metrics, and defined go/no-go criteria to ensure the new system is ready to take over as the single source of truth.

Strategic Objectives of Parallel Running

The core objective of parallel running is to de-risk the cutover by providing empirical evidence that the new ERP system functions correctly under real-world conditions. Unlike sandbox testing, which uses static data, parallel running exposes the system to dynamic, real-time transactions. This phase serves three main strategic purposes: data validation, process verification, and user confidence building. Data validation ensures that migrated records remain accurate and consistent across both systems. Process verification confirms that business workflows, such as order-to-cash or procure-to-pay, execute correctly in the new environment. User confidence building involves training end-users in the live environment, reducing resistance to change and identifying usability issues early.

Data Integrity and Reconciliation

Data integrity is the most critical aspect of parallel running. Organizations must establish a rigorous reconciliation process to compare key data points between the legacy and new systems. This includes general ledger balances, inventory quantities, customer account balances, and vendor payment statuses. Discrepancies must be logged, analyzed, and resolved before proceeding to the next phase. The reconciliation process should be automated where possible to reduce manual error and increase efficiency. Regular reporting on reconciliation status helps project managers track progress and identify systemic issues that may require technical intervention.

Process Workflow Verification

Beyond data, parallel running validates that business processes function as intended. This involves executing standard and exception scenarios in the new system while comparing outcomes with the legacy system. For example, if a purchase order is created in both systems, the resulting invoices, receipts, and payments should match. Any deviations indicate potential configuration errors, missing customizations, or integration failures. This phase also tests the robustness of the new system under peak load, ensuring that performance does not degrade during high-transaction periods.

Planning the Parallel Run Phase

Successful parallel running requires meticulous planning. The project team must define the scope, duration, and resources required for this phase. The scope should include all critical business processes and data entities that will be migrated. The duration depends on the complexity of the ERP system and the volume of transactions, typically ranging from two to six weeks. Resources include IT staff for technical support, business users for transaction processing, and finance teams for reconciliation. A detailed timeline with milestones and deliverables ensures that all stakeholders are aligned and accountable.

Defining Scope and Duration

The scope of parallel running should be comprehensive yet manageable. It should cover all modules that are being migrated, including finance, supply chain, human resources, and customer relationship management. The duration should be sufficient to capture a full business cycle, including month-end and year-end closing processes if applicable. For example, if the migration occurs mid-month, the parallel run should extend through the month-end close to validate financial reporting. This ensures that the new system can handle complex accounting entries and reporting requirements.

Resource Allocation and Roles

Clear role definitions are essential for effective parallel running. The project manager oversees the overall process and coordinates between IT and business teams. IT staff provide technical support, monitor system performance, and resolve technical issues. Business users process transactions in both systems and report discrepancies. Finance teams perform reconciliation and validate financial data. A dedicated support team should be available to address user queries and provide training. This structure ensures that all aspects of the parallel run are covered and that issues are resolved promptly.

Technical Execution and Monitoring

During parallel running, the new ERP system must be configured to operate independently while mirroring the legacy system's transactions. This requires careful setup of data interfaces and integration points to ensure that data flows correctly between systems. Monitoring tools should be deployed to track system performance, error rates, and transaction volumes. Real-time dashboards provide visibility into key metrics, enabling the project team to identify and address issues proactively. Technical execution also involves managing user access and security to prevent unauthorized changes to the new system during the parallel run.

System Configuration and Integration

The new ERP system must be configured to accept and process transactions in the same manner as the legacy system. This includes setting up chart of accounts, item masters, customer and vendor records, and business rules. Integration points with external systems, such as payment gateways, shipping carriers, and CRM platforms, must be tested to ensure seamless data exchange. Any customizations or third-party add-ons must be verified for compatibility with the new system. This phase is critical for ensuring that the new system can handle all business requirements without gaps or errors.

Performance Monitoring and Alerting

Performance monitoring is essential to detect and resolve issues before they impact business operations. Key performance indicators (KPIs) include transaction processing time, system uptime, error rates, and resource utilization. Alerts should be configured to notify the IT team of any anomalies, such as high error rates or slow response times. This proactive approach minimizes downtime and ensures that the new system remains stable throughout the parallel run. Performance data also provides a baseline for post-migration optimization and capacity planning.

Data Reconciliation and Discrepancy Management

Data reconciliation is the heart of parallel running. It involves comparing data from the legacy and new systems to identify and resolve discrepancies. This process should be systematic and documented, with clear criteria for what constitutes a discrepancy and how it should be resolved. Discrepancies can arise from data mapping errors, transformation issues, or process differences. Each discrepancy must be logged in a tracking system, assigned to a responsible party, and resolved within a defined timeframe. Regular reconciliation reports provide visibility into the status of discrepancies and help the project team make informed decisions about cutover readiness.

Reconciliation Methodology

The reconciliation methodology should be tailored to the specific business processes and data entities involved. For financial data, reconciliation should focus on general ledger balances, sub-ledger accounts, and financial statements. For supply chain data, it should cover inventory levels, purchase orders, and sales orders. For customer data, it should include account balances, credit limits, and order history. Automated reconciliation tools can streamline this process by comparing data sets and highlighting differences. Manual review is still necessary to investigate and resolve complex discrepancies that require business judgment.

Discrepancy Resolution Process

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SysGenPro Editorial

SysGenPro Editorial

Platform & solutions team

Practical guidance on ERP, AI automation, cloud deployment and enterprise transformation from the SysGenPro team.

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